Semi-Automatic Query Expansion using Most Discriminant Words

Most casual users of IR systems type short queries. With current indexing technologies, short queries return enormous amount of results that may be impossible to examinate carefully. If users not find what they are looking for between the first 10/100 results, they may stop searching, losing the important results wrongly ranked by the search engine. While users generally know what they are looking for, the task of express their desires in a compact, precise, written form, i.e. the query, represent a real problem. Word usage is in fact both domain and user dependent, and may easily mislead the search engine. In this report I investigate a new method for query expansion, that exploiting the user’s feedback on some discriminant words, try to increase the focus on the user’s